The announcement that SuperPlane has raised a $2.6 million pre-seed round signals a shift in how engineering organizations think about production. As AI accelerates code creation, the real bottleneck is moving from writing software to operating it safely at scale. Darko Fabijan and Marko Anastasov, previously behind Semaphore, have assembled a team of veterans to build an open-source control plane that promises to bring determinism and intelligent automation to that final mile.

The end of manual operations?

Today’s engineering teams ship more code, across more systems, faster than ever before. Yet the operational layer beneath it—deployments, infrastructure changes, incident response, approvals—remains fragmented and largely manual. Scattered scripts, tribal knowledge, and ad hoc coordination make the production path fragile. SuperPlane addresses this directly: it offers an AI-first operational layer where agents can propose and coordinate actions across the tools teams already use (GitHub, Slack, PagerDuty, Datadog, OpenAI, Claude), while human engineers stay in control.

The idea of a control plane is familiar from Kubernetes, but applying it with an event-driven architecture and policy-based governance is the novelty. SuperPlane isn’t a generic orchestrator; it’s designed to give AI operational context, policies, and guardrails so that automation proposals are auditable and reversible. The stated goal is to turn operational knowledge—currently buried in scripts and unwritten procedures—into systems that are structured, reviewable, and executable at an organizational scale.

Open source and infrastructure sovereignty

The decision to release everything as open source (the code is already on GitHub) has real implications for those evaluating on-premise or hybrid deployments. A self-hosted control plane means an organization keeps full sovereignty over its operational data, without depending on third-party cloud services to run its own operations. In regulated or air-gapped environments, the ability to run SuperPlane behind a firewall without exposing sensitive metadata is a concrete advantage. AI-RADAR, which closely tracks the choices of those who prioritize data residency, observes how this approach fits a broader trend: bringing AI benefits to where compliance requirements live, rather than outsourcing everything to an external SaaS.

Of course, adopting a new control plane carries integration costs and a learning curve, especially in heavily customized organizations. SuperPlane’s promise is to reduce complexity by aggregating over 30 native integrations and 300 components, but the real test will be its ability to adapt to real-world flows without imposing a rigid model.

From code writing to operational management, the team behind the bet

The round was led by Credo Ventures, with participation from First Momentum Ventures and a list of angel investors that includes figures like Mirko Novakovic (Dash0), Tomas Kratky (Manta), and Peter Zaitsev (Percona). The fact that many investors come from the developer tools and infrastructure world is a signal: the industry recognizes that the next productivity leap won’t come from a new IDE or a coding assistant, but from a radical rethinking of how AI can co-pilot the management of complex systems.

Darko Fabijan and Marko Anastasov previously built Semaphore, a CI/CD platform used by Confluent and Replit. With SuperPlane, they aim to go beyond code delivery and tackle the operational problem that explodes when AI generates code ten times faster than humans. The pre-seed funding will accelerate product development, deepen work with design partners and early customers, and grow the open-source community. The bet is clear: make production operations as scalable and governable as the software that powers them.